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We conducted a cohort study nested in a randomised controlled trial. A random group of GPs were offered a technological upgrade consisting of direct access to chest LDCT combined with a simple Continuing Medical Education (CME) meeting on lung cancer diagnosis.
The study took place in a large catchment area around Aarhus University Hospital in the Central Denmark Region during 19 months (November 2011 to June 2013). Denmark has a tax-financed healthcare system with free access to medical advice and treatment in general practices and hospitals. GPs act as gatekeepers to specialized investigations and hospitals referrals. Before November in 2011, the GPs in the area had three diagnostic work-up possibilities for patients with respiratory symptoms. They could either refer to 1) a chest radiograph 2) the Department of Pulmonary Medicine within normal waiting list or 3) a fast-track pathway. A valid indication for fast track was either an abnormal chest radiograph or certain symptoms (e.g. haemoptysis of >one week’s duration or persistent coughing >four weeks). The GPs were not allowed to refer directly to a CT.
All GPs referring to the Department of Pulmonary Medicine. A total of 266 GPs organised into 119 general practices, were randomised into two groups. The unit of randomisation was the practice address. The randomisation was performed by a Data Manager using Stata 12.0. The 119 practices were allocated a random number between zero and one and then listed from lowest to highest value. The top 60 practice addresses formed the intervention group. In this paper, we include only the intervention group.
Six times within an 3-month period, the intervention GPs were informed about the opportunity to refer their patients to a direct chest CT. The letters included information concerning the referral procedures and specific indications for CT requests. These indications embraced a wide range of concerns; the only exception was patients who met the indication for a fast-track referral. The idea was to let the GPs substitute the radiograph with a chest LDCT when wanting to rule out lung cancer. The GPs were also invited to participate in one of eight offered 1-hour small-group-based CME meetings. The meetings were held during the initial two months. The content of the meeting focused on state-of-the-art knowledge on earlier detection of lung cancer. Algorithms for positive predictive values in primary care were used [10], [16]. In addition, participants received information about the CTs, how to use them and how to interpret the reports.
Chest CT, review and lung cancer diagnosis: The Department of Radiology, Aarhus University Hospital, carried out the CTs. Scans were performed on a Brilliance 64 CT Scanner by Philips with a beam collimation of 64×0.625, 2 mm slice thickness, 1 mm increment, 1 pitch and a rotation time of 0.75 s. The effective radiation dose (Monte Carlo simulation program CT-Expo v. 2.1) was 2–3 mSv. Intravenous contrast medium was not administered. The time limit from referral to performed CT was a maximum of two working days. The CT report was made by three sub-specialised radiologists. The day after the scan, the report combined with the patient’s medical history resulted in a recommendation drawn up at a conference between radiologists and chest physicians. This recommendation was forwarded electronically to the GP, who was responsible for informing the patient of the results and referring the patient to further diagnostic work-up if necessary. If lung nodules (4–10 mm), which could not be categorised as benign, were detected, the GP was responsible for referring the patient to a follow-up program (3, 6 or 12 months after the first scan) based on characteristics of the identified nodules [17]. The follow-up program was decided by the chest physicians. If the CT scan revealed any suspicion of lung cancer, the patients were referred through the fast track to standard diagnostic work-up at the Department of Pulmonary Medicine by the GP. This included contrast enhanced multi detection CT (including PET/CT if surgery was an option). Furthermore, histologic/cytologic diagnosis was obtained by the least invasive method, which was usually either bronchoscopy with biopsies, fine needle aspiration (FNA) in association with endoscopic ultrasound or endobronchial ultrasound, or transthoracic FNA. The final staging was decided by a multi-disciplinary team based on clinical (cTNM) information. The lung cancers were staged according to the 7th TNM Classification of Malignant Tumors [18]. Early stage cancers were defined as stage I–IIB. Early stage patients were offered surgical resection according to Danish guidelines.
The sample size was calculated for the randomised trial and the numbers of GPs needed in the intervention arm was guided by the calculation. In 2008, half of the Danish lung patients waited 34 days or more (the median) from first presentation to primary care until diagnosis of lung cancer [19]. We hoped to be able to show a decrease in the diagnostic interval to a level where only 25% of the patients had to wait for 34 days or more. Thus, the proportion waiting 34 days or more should be halved. With a one-sided alpha of 5% and a power of 80%, we had to include 54 lung cancer patients in each arm with a 1∶1 randomisation. It can be assumed that lung cancer patients are randomly distributed among GPs. There could, however, be a higher incidence of cancer in some areas with many smokers and in practices with many elderly patients. To account for an unknown intra-cluster correlation coefficient (ICC), we counted on a design effect of 1.25 [20]. Given the design effect, we had to include a total of 54*2*1.25 = 135 lung cancer patients with questionnaire data and GP involvement in the diagnosis.
Primary outcomes were characteristics of patients referred and GP variation in use, while secondary outcomes were amount of diagnostic work-up needed and cancer incidence. Finally, we examined the use of the fast-track referral option for suspected lung cancer and the proportion of lung cancer (the positive predictive value (PPV)) in order to evaluate the possible effect of the CME on this aspect.
Based on the GPs’ referral notes, we obtained data on the patients symptoms, known diseases and smoking history. We obtained the medical records resulting from completed CT scans, including the consensus evaluation between radiologist and pulmonary physician. The Danish Lung Cancer Register (DLCR) was used for information on subsequent diagnosis of lung cancer (International Classification of Diseases 10: C34.0-9). The DLCR was established in 2001 as a national database. Since 2003, the registered data have covered more than 90% of all lung cancer cases in Denmark [21]. Patients referred to fast-track evaluation for lung cancer are coded DZ 03.1B (lung cancer observation). This code, combined with a unique GP number, gave information about referral to the fast-track pathway. The Danish Cancer Registry (DCR) was used to obtain information about previous cancer (except non-melanoma skin cancer (C44)). The registry contains information about Danish cancer patients, their date of diagnosis and tumour characteristics. Since 1987, reporting to the DCR has been mandatory [22]. We used the Danish Deprivation Index (DADI) to gather information about deprivation rates in the different GP clinics. The index consists of eight variables resulting in a value number between 10 and 100; the higher the number, the greater the extent of deprivation in the practice population. The variables used are: (i) Proportion of adults aged 20–59 with no employment, (ii) proportion of adults aged 25–59 with no professional education, (iii) proportion of adults aged 25–59 with low income, (iv) proportion of adults aged 18–59 receiving public welfare payments (transfer income or social benefits), (v) proportion of children from parents with no education and no professional skills, (vi) proportion of immigrants, (vii) proportion of adults aged 30+ living alone and (viii) proportion of adults aged 70+ with low income ( = the lowest national quartile). The Health Service Registry was used to gather information about GP list size and age/gender distribution of the patients listed with the GP [23]. The Danish civil registration number, a unique personal identification number, was used to link registers [24].
Patient characteristics were described and duration of symptoms was calculated as medians with interquartile intervals (IQI). GP groups were compared using the Wilcoxon’s rank-sum test for ordinal or continuous data or Pearsons χ2 test for unordered or dichotomous categorical data. Referral rates were calculated based on number of patients referred by the GP per project month per list size (patients aged 25 years and above). We used indirect sex-age standardisation to compare the referral rates between CME-attending GPs and non-attending GPs. We used the CME-attending GPs as the standard population and calculated the referral rates for the patients listed with the GPs in 10-years age groups (25–34, 35–44, etc.). These expected rates were then applied to the non-attending GP list. We calculated the standardized referral rate ratio as number of referrals divided by expected numbers if the age-sex specific rates were the same as those of the standard population. The age-sex referral rate was then obtained by multiplying the referral rate ratio by the crude referral rate of the standard population. Data were analysed using the statistical software Stata 12.0 (StataCorp LP, TX, USA). The protocol for the randomised trial and supporting TREND checklist for this study are available as supporting information; see Checklist S1 and Protocol S1.
The study was approved by the Danish Data Protection Agency (ref.no: 2011-41-6872) and the Danish Health and Medicines Authority (ref.no: 7-604-04-2/357/KWH). According to the Research Ethics Committee of the Central Denmark Region, the Danish Act on Research Ethics Review of Health Research Projects did not apply to this project (ref.no: 118/2011) as CT is already a widely used technology.
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